A number of systems have been developed in recent years, mostly for military and transportation industry purposes, which involve the electronic projection, on a screen located in a vehicle or aircraft, of a map showing relevant information regarding the area in which the vehicle or aircraft is traveling. Such maps are known as digital maps because they are composed, like a video image, of a large number of pixels whose color is digitally encoded.
Digital maps are conventionally produced by scanning printed paper maps to generate a digital electronic image of the paper map. The quality of the digitization is adversely affected by a variety of factors relating to the printing and scanning process. These factors are principally the following:
a) The paper map has defects introduced by the printing process (e.g. uneven inking or ink smears). PA1 b) Noise is introduced by the scanning process. In other words, the color that is sampled for a pixel will not be completely accurate. PA1 c) When the paper map is printed, some regions are represented by numerous small dots of similar or different colors. On physical paper maps, these regions appear to the eye as being of a single solid color, but they show up as noise when digitized. PA1 a) the map appears noisy on the screen, especially on a close-in zoom. For example, an ocean area, which one would expect to be solid blue, appears on the screen as several different shades of blue with white dots scattered in regular patterns. PA1 b) The compression efficiency is decreased. These maps take up considerable room on the computer's hard disk, so it is desirable to compress them as much as possible. The more uniformly colored the map is, the more it can be compressed.
The limited quality of the digitization causes two principal problems when the digitized data is imaged on a computer monitor:
Consequently, although the prior art digital maps have proven generally suitable for their intended purposes, they possess inherent deficiencies which detract from their overall effectiveness.
The prior art has attempted to solve this problem by traditional image smoothing methods using, for example, averaging or interpolating techniques which work well on "real" images such as scenes. These methods, however, can have undesirable side effects when used on "artificial" images such as maps, because they tend to blur fine-print annotations which are a vital component of maps.
It is thus desirable to provide a way to smooth out the noisy appearance of the imaged map, and to so modify it as to maximize its compressibility, yet without degrading the map annotations. Although this is a well recognized problem, the proposed solutions have, to date, been ineffective in providing a satisfactory remedy.